Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit [W] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 5 other fieldsHigh correlation
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 3 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°] and 2 other fieldsHigh correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W] and 1 other fieldsHigh correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 8 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 1 other fieldsHigh correlation
Grid Production ReactivePower StdDev [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with Active power limit [W] and 5 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with Active power limit [W] and 5 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with Production LatestAverage Active Power Gen 1 Avg. [W]High correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 4 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with Active power limit [W] and 5 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with Active power limit [W] and 5 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with Active power limit [W] and 5 other fieldsHigh correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with Active power limit [W] and 5 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (60.1%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (53.1%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (53.2%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (54.4%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (69.0%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (74.1%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (75.7%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (72.9%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (58.1%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (76.2%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (74.6%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (56.3%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (65.2%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (69.5%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (64.9%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (63.0%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (61.5%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (55.6%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (69.4%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (52.2%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (57.6%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (88.7%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (86.0%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.5%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (70.8%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (81.3%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (84.2%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (69.4%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (51.2%) Imbalance
Grid RotorInvPhase2 Temp. Avg. [°C] is highly imbalanced (64.1%) Imbalance
Grid RotorInvPhase3 Temp. Avg. [°C] is highly imbalanced (59.7%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (79.0%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (70.0%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (96.1%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.4%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (92.6%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (92.0%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (77.3%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (73.8%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (74.8%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (71.2%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (70.4%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (57.5%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (76.8%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (56.3%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (82.1%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (76.9%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (76.4%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (79.0%) Imbalance
Active power limit [W] is highly imbalanced (96.0%) Imbalance
Active power limit source is highly imbalanced (99.0%) Imbalance
Power factor set point is highly imbalanced (99.0%) Imbalance
Power factor set point source is highly imbalanced (99.0%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (92.1%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (84.1%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (76.1%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (66.1%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (83.8%) Imbalance
Controller VCP WaterTemp. Avg. [°C] is highly imbalanced (58.8%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (69.1%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (55.3%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (56.6%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (58.8%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (81.0%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (81.1%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (78.8%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (58.5%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (96.6%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (96.5%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (96.5%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (93.7%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (80.8%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (62.2%) Imbalance
HourCounters Average Yaw Avg. [h] is highly imbalanced (53.3%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (99.5%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (94.7%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (65.0%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (94.0%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (68.8%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (84.9%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (75.5%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (80.1%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (65.8%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (56.0%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (57.4%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.8%) Imbalance
Total Active power [W] is highly imbalanced (99.7%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (96.9%) Imbalance
Total reactive power [var] is highly imbalanced (95.2%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-15 12:15:13.257290
Analysis finished2025-05-15 12:15:40.842299
Duration27.59 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-15T14:15:40.883579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-15T14:15:40.966459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24138 
1
 
2070

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24138
92.1%
1 2070
 
7.9%

Length

2025-05-15T14:15:41.042361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.078194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24138
92.1%
1 2070
 
7.9%

Most occurring characters

ValueCountFrequency (%)
0 24138
92.1%
1 2070
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24138
92.1%
1 2070
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24138
92.1%
1 2070
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24138
92.1%
1 2070
 
7.9%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23586 
1
2622 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23586
90.0%
1 2622
 
10.0%

Length

2025-05-15T14:15:41.120633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.158918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23586
90.0%
1 2622
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23586
90.0%
1 2622
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23586
90.0%
1 2622
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23586
90.0%
1 2622
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23586
90.0%
1 2622
 
10.0%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23598 
1
2610 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23598
90.0%
1 2610
 
10.0%

Length

2025-05-15T14:15:41.203389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.240048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23598
90.0%
1 2610
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23598
90.0%
1 2610
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23598
90.0%
1 2610
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23598
90.0%
1 2610
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23598
90.0%
1 2610
 
10.0%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23694 
1
2514 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23694
90.4%
1 2514
 
9.6%

Length

2025-05-15T14:15:41.286612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.323368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23694
90.4%
1 2514
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23694
90.4%
1 2514
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23694
90.4%
1 2514
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23694
90.4%
1 2514
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23694
90.4%
1 2514
 
9.6%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24748 
1
 
1460

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24748
94.4%
1 1460
 
5.6%

Length

2025-05-15T14:15:41.369595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.405672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24748
94.4%
1 1460
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 24748
94.4%
1 1460
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24748
94.4%
1 1460
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24748
94.4%
1 1460
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24748
94.4%
1 1460
 
5.6%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25060 
1
 
1148

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25060
95.6%
1 1148
 
4.4%

Length

2025-05-15T14:15:41.448043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.485654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25060
95.6%
1 1148
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25060
95.6%
1 1148
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25060
95.6%
1 1148
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25060
95.6%
1 1148
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25060
95.6%
1 1148
 
4.4%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25158 
1
 
1050

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Length

2025-05-15T14:15:41.528812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.565588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25158
96.0%
1 1050
 
4.0%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24993 
1
 
1215

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Length

2025-05-15T14:15:41.610227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.646106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24993
95.4%
1 1215
 
4.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23985 
1
 
2223

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23985
91.5%
1 2223
 
8.5%

Length

2025-05-15T14:15:41.689232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.727778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23985
91.5%
1 2223
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23985
91.5%
1 2223
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23985
91.5%
1 2223
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23985
91.5%
1 2223
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23985
91.5%
1 2223
 
8.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25184 
1
 
1024

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25184
96.1%
1 1024
 
3.9%

Length

2025-05-15T14:15:41.772382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.808506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25184
96.1%
1 1024
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25184
96.1%
1 1024
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25184
96.1%
1 1024
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25184
96.1%
1 1024
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25184
96.1%
1 1024
 
3.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22119 
1
4089 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22119
84.4%
1 4089
 
15.6%

Length

2025-05-15T14:15:41.855274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.893327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22119
84.4%
1 4089
 
15.6%

Most occurring characters

ValueCountFrequency (%)
0 22119
84.4%
1 4089
 
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22119
84.4%
1 4089
 
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22119
84.4%
1 4089
 
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22119
84.4%
1 4089
 
15.6%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25092 
1
 
1116

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25092
95.7%
1 1116
 
4.3%

Length

2025-05-15T14:15:41.937809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:41.975580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25092
95.7%
1 1116
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25092
95.7%
1 1116
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25092
95.7%
1 1116
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25092
95.7%
1 1116
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25092
95.7%
1 1116
 
4.3%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:42.018363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.052250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:42.093644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.127223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23849 
1
 
2359

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23849
91.0%
1 2359
 
9.0%

Length

2025-05-15T14:15:42.166865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.205378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23849
91.0%
1 2359
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23849
91.0%
1 2359
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23849
91.0%
1 2359
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23849
91.0%
1 2359
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23849
91.0%
1 2359
 
9.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24500 
1
 
1708

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24500
93.5%
1 1708
 
6.5%

Length

2025-05-15T14:15:42.249939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.285995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24500
93.5%
1 1708
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24500
93.5%
1 1708
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24500
93.5%
1 1708
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24500
93.5%
1 1708
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24500
93.5%
1 1708
 
6.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:42.330774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.364321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24782 
1
 
1426

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24782
94.6%
1 1426
 
5.4%

Length

2025-05-15T14:15:42.404006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.441728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24782
94.6%
1 1426
 
5.4%

Most occurring characters

ValueCountFrequency (%)
0 24782
94.6%
1 1426
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24782
94.6%
1 1426
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24782
94.6%
1 1426
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24782
94.6%
1 1426
 
5.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24475 
1
 
1733

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24475
93.4%
1 1733
 
6.6%

Length

2025-05-15T14:15:42.484298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.520463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24475
93.4%
1 1733
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 24475
93.4%
1 1733
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24475
93.4%
1 1733
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24475
93.4%
1 1733
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24475
93.4%
1 1733
 
6.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24343 
1
 
1865

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Length

2025-05-15T14:15:42.565626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.602090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24343
92.9%
1 1865
 
7.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24238 
1
 
1970

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Length

2025-05-15T14:15:42.644585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.682331image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring characters

ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23793 
1
2415 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Length

2025-05-15T14:15:42.725378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.762134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring characters

ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23793
90.8%
1 2415
 
9.2%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24776 
1
 
1432

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Length

2025-05-15T14:15:42.808915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.845648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23515 
1
2693 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23515
89.7%
1 2693
 
10.3%

Length

2025-05-15T14:15:42.889093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:42.927824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23515
89.7%
1 2693
 
10.3%

Most occurring characters

ValueCountFrequency (%)
0 23515
89.7%
1 2693
 
10.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23515
89.7%
1 2693
 
10.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23515
89.7%
1 2693
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23515
89.7%
1 2693
 
10.3%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22747 
1
3461 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22747
86.8%
1 3461
 
13.2%

Length

2025-05-15T14:15:42.972628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.009491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22747
86.8%
1 3461
 
13.2%

Most occurring characters

ValueCountFrequency (%)
0 22747
86.8%
1 3461
 
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22747
86.8%
1 3461
 
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22747
86.8%
1 3461
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22747
86.8%
1 3461
 
13.2%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23950 
1
 
2258

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Length

2025-05-15T14:15:43.209677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.246062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23950
91.4%
1 2258
 
8.6%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23080 
1
3128 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23080
88.1%
1 3128
 
11.9%

Length

2025-05-15T14:15:43.290506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.329455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23080
88.1%
1 3128
 
11.9%

Most occurring characters

ValueCountFrequency (%)
0 23080
88.1%
1 3128
 
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23080
88.1%
1 3128
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23080
88.1%
1 3128
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23080
88.1%
1 3128
 
11.9%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25811 
1
 
397

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25811
98.5%
1 397
 
1.5%

Length

2025-05-15T14:15:43.374005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.410604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25811
98.5%
1 397
 
1.5%

Most occurring characters

ValueCountFrequency (%)
0 25811
98.5%
1 397
 
1.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25811
98.5%
1 397
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25811
98.5%
1 397
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25811
98.5%
1 397
 
1.5%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25690 
1
 
518

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25690
98.0%
1 518
 
2.0%

Length

2025-05-15T14:15:43.454896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.490737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25690
98.0%
1 518
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25690
98.0%
1 518
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25690
98.0%
1 518
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25690
98.0%
1 518
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25690
98.0%
1 518
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25929 
1
 
279

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25929
98.9%
1 279
 
1.1%

Length

2025-05-15T14:15:43.532997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.571100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25929
98.9%
1 279
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25929
98.9%
1 279
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25929
98.9%
1 279
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25929
98.9%
1 279
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25929
98.9%
1 279
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24862 
1
 
1346

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24862
94.9%
1 1346
 
5.1%

Length

2025-05-15T14:15:43.614484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.650195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24862
94.9%
1 1346
 
5.1%

Most occurring characters

ValueCountFrequency (%)
0 24862
94.9%
1 1346
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24862
94.9%
1 1346
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24862
94.9%
1 1346
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24862
94.9%
1 1346
 
5.1%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25462 
1
 
746

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25462
97.2%
1 746
 
2.8%

Length

2025-05-15T14:15:43.694537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.731610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25462
97.2%
1 746
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25462
97.2%
1 746
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25462
97.2%
1 746
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25462
97.2%
1 746
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25462
97.2%
1 746
 
2.8%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25606 
1
 
602

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25606
97.7%
1 602
 
2.3%

Length

2025-05-15T14:15:43.775568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.812122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25606
97.7%
1 602
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 25606
97.7%
1 602
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25606
97.7%
1 602
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25606
97.7%
1 602
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25606
97.7%
1 602
 
2.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23042 
1
3166 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23042
87.9%
1 3166
 
12.1%

Length

2025-05-15T14:15:43.855461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.894821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23042
87.9%
1 3166
 
12.1%

Most occurring characters

ValueCountFrequency (%)
0 23042
87.9%
1 3166
 
12.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23042
87.9%
1 3166
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23042
87.9%
1 3166
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23042
87.9%
1 3166
 
12.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:43.939580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:43.973229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24774 
1
 
1434

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24774
94.5%
1 1434
 
5.5%

Length

2025-05-15T14:15:44.014551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.050366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24774
94.5%
1 1434
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24774
94.5%
1 1434
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24774
94.5%
1 1434
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24774
94.5%
1 1434
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24774
94.5%
1 1434
 
5.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23429 
1
2779 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23429
89.4%
1 2779
 
10.6%

Length

2025-05-15T14:15:44.092885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.131194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23429
89.4%
1 2779
 
10.6%

Most occurring characters

ValueCountFrequency (%)
0 23429
89.4%
1 2779
 
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23429
89.4%
1 2779
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23429
89.4%
1 2779
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23429
89.4%
1 2779
 
10.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24422 
1
 
1786

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24422
93.2%
1 1786
 
6.8%

Length

2025-05-15T14:15:44.175850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.211645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24422
93.2%
1 1786
 
6.8%

Most occurring characters

ValueCountFrequency (%)
0 24422
93.2%
1 1786
 
6.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24422
93.2%
1 1786
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24422
93.2%
1 1786
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24422
93.2%
1 1786
 
6.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24104 
1
 
2104

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24104
92.0%
1 2104
 
8.0%

Length

2025-05-15T14:15:44.255687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.292578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24104
92.0%
1 2104
 
8.0%

Most occurring characters

ValueCountFrequency (%)
0 24104
92.0%
1 2104
 
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24104
92.0%
1 2104
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24104
92.0%
1 2104
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24104
92.0%
1 2104
 
8.0%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25340 
1
 
868

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25340
96.7%
1 868
 
3.3%

Length

2025-05-15T14:15:44.337272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.374953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25340
96.7%
1 868
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25340
96.7%
1 868
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25340
96.7%
1 868
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25340
96.7%
1 868
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25340
96.7%
1 868
 
3.3%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24812 
1
 
1396

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24812
94.7%
1 1396
 
5.3%

Length

2025-05-15T14:15:44.417580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.453507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24812
94.7%
1 1396
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 24812
94.7%
1 1396
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24812
94.7%
1 1396
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24812
94.7%
1 1396
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24812
94.7%
1 1396
 
5.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26097 
1
 
111

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Length

2025-05-15T14:15:44.497958image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.534017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25966 
1
 
242

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25966
99.1%
1 242
 
0.9%

Length

2025-05-15T14:15:44.576811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.614874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25966
99.1%
1 242
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25966
99.1%
1 242
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25966
99.1%
1 242
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25966
99.1%
1 242
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25966
99.1%
1 242
 
0.9%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25971 
1
 
237

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Length

2025-05-15T14:15:44.657369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.693578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25971
99.1%
1 237
 
0.9%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25948 
1
 
260

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25948
99.0%
1 260
 
1.0%

Length

2025-05-15T14:15:44.738261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.774249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25948
99.0%
1 260
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25948
99.0%
1 260
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25948
99.0%
1 260
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25948
99.0%
1 260
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25948
99.0%
1 260
 
1.0%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25245 
1
 
963

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25245
96.3%
1 963
 
3.7%

Length

2025-05-15T14:15:44.817105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.855173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25245
96.3%
1 963
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25245
96.3%
1 963
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25245
96.3%
1 963
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25245
96.3%
1 963
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25245
96.3%
1 963
 
3.7%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25044 
1
 
1164

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Length

2025-05-15T14:15:44.898567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:44.935030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25101 
1
 
1107

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25101
95.8%
1 1107
 
4.2%

Length

2025-05-15T14:15:44.979443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.015482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25101
95.8%
1 1107
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25101
95.8%
1 1107
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25101
95.8%
1 1107
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25101
95.8%
1 1107
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25101
95.8%
1 1107
 
4.2%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24888 
1
 
1320

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24888
95.0%
1 1320
 
5.0%

Length

2025-05-15T14:15:45.058368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.096162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24888
95.0%
1 1320
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24888
95.0%
1 1320
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24888
95.0%
1 1320
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24888
95.0%
1 1320
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24888
95.0%
1 1320
 
5.0%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24841 
1
 
1367

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Length

2025-05-15T14:15:45.138929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.175247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring characters

ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24841
94.8%
1 1367
 
5.2%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23936 
1
 
2272

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23936
91.3%
1 2272
 
8.7%

Length

2025-05-15T14:15:45.219633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.256374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23936
91.3%
1 2272
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23936
91.3%
1 2272
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23936
91.3%
1 2272
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23936
91.3%
1 2272
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23936
91.3%
1 2272
 
8.7%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25220 
1
 
988

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Length

2025-05-15T14:15:45.301105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.339012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25220
96.2%
1 988
 
3.8%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23845 
1
 
2363

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23845
91.0%
1 2363
 
9.0%

Length

2025-05-15T14:15:45.382340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.419078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23845
91.0%
1 2363
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23845
91.0%
1 2363
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23845
91.0%
1 2363
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23845
91.0%
1 2363
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23845
91.0%
1 2363
 
9.0%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22708 
1
3500 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22708
86.6%
1 3500
 
13.4%

Length

2025-05-15T14:15:45.465668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.502390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22708
86.6%
1 3500
 
13.4%

Most occurring characters

ValueCountFrequency (%)
0 22708
86.6%
1 3500
 
13.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22708
86.6%
1 3500
 
13.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22708
86.6%
1 3500
 
13.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22708
86.6%
1 3500
 
13.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22776 
1
3432 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22776
86.9%
1 3432
 
13.1%

Length

2025-05-15T14:15:45.547151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.585668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22776
86.9%
1 3432
 
13.1%

Most occurring characters

ValueCountFrequency (%)
0 22776
86.9%
1 3432
 
13.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22776
86.9%
1 3432
 
13.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22776
86.9%
1 3432
 
13.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22776
86.9%
1 3432
 
13.1%

Grid Production ReactivePower StdDev [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21511 
1
4697 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21511
82.1%
1 4697
 
17.9%

Length

2025-05-15T14:15:45.630898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.667424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21511
82.1%
1 4697
 
17.9%

Most occurring characters

ValueCountFrequency (%)
0 21511
82.1%
1 4697
 
17.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21511
82.1%
1 4697
 
17.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21511
82.1%
1 4697
 
17.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21511
82.1%
1 4697
 
17.9%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25500 
1
 
708

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25500
97.3%
1 708
 
2.7%

Length

2025-05-15T14:15:45.714368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.750408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25500
97.3%
1 708
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25500
97.3%
1 708
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25500
97.3%
1 708
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25500
97.3%
1 708
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25500
97.3%
1 708
 
2.7%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25224 
1
 
984

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Length

2025-05-15T14:15:45.792912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.830992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25197 
1
 
1011

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Length

2025-05-15T14:15:45.874847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.910864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25197
96.1%
1 1011
 
3.9%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25341 
1
 
867

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25341
96.7%
1 867
 
3.3%

Length

2025-05-15T14:15:45.956049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:45.991775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25341
96.7%
1 867
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25341
96.7%
1 867
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25341
96.7%
1 867
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25341
96.7%
1 867
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25341
96.7%
1 867
 
3.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.034523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.069974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.259663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.293489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.334479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.368219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.407651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.442936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.482596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.516073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.557222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.591316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.630725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.666189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.706014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.739583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26096 
1
 
112

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26096
99.6%
1 112
 
0.4%

Length

2025-05-15T14:15:46.781313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.817325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26096
99.6%
1 112
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26096
99.6%
1 112
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26096
99.6%
1 112
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26096
99.6%
1 112
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26096
99.6%
1 112
 
0.4%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26186 
1
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Length

2025-05-15T14:15:46.860677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.901552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:46.944811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:46.978634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26186 
1
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Length

2025-05-15T14:15:47.019991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.056447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26186 
1
 
22

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Length

2025-05-15T14:15:47.099030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.136834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26186
99.9%
1 22
 
0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25954 
1
 
254

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25954
99.0%
1 254
 
1.0%

Length

2025-05-15T14:15:47.179664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.215873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25954
99.0%
1 254
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25954
99.0%
1 254
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25954
99.0%
1 254
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25954
99.0%
1 254
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25954
99.0%
1 254
 
1.0%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25602 
1
 
606

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25602
97.7%
1 606
 
2.3%

Length

2025-05-15T14:15:47.260026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.296194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25602
97.7%
1 606
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 25602
97.7%
1 606
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25602
97.7%
1 606
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25602
97.7%
1 606
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25602
97.7%
1 606
 
2.3%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25178 
1
 
1030

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25178
96.1%
1 1030
 
3.9%

Length

2025-05-15T14:15:47.338917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.376714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25178
96.1%
1 1030
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25178
96.1%
1 1030
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25178
96.1%
1 1030
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25178
96.1%
1 1030
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25178
96.1%
1 1030
 
3.9%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24557 
1
 
1651

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Length

2025-05-15T14:15:47.419405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.455434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24557
93.7%
1 1651
 
6.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25586 
1
 
622

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25586
97.6%
1 622
 
2.4%

Length

2025-05-15T14:15:47.499810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.535874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25586
97.6%
1 622
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25586
97.6%
1 622
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25586
97.6%
1 622
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25586
97.6%
1 622
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25586
97.6%
1 622
 
2.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24036 
1
 
2172

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24036
91.7%
1 2172
 
8.3%

Length

2025-05-15T14:15:47.578778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.617410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24036
91.7%
1 2172
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24036
91.7%
1 2172
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24036
91.7%
1 2172
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24036
91.7%
1 2172
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24036
91.7%
1 2172
 
8.3%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24757 
1
 
1451

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24757
94.5%
1 1451
 
5.5%

Length

2025-05-15T14:15:47.662027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.698110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24757
94.5%
1 1451
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24757
94.5%
1 1451
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24757
94.5%
1 1451
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24757
94.5%
1 1451
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24757
94.5%
1 1451
 
5.5%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:47.742415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.776089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23769 
1
2439 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23769
90.7%
1 2439
 
9.3%

Length

2025-05-15T14:15:47.815825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.854683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23769
90.7%
1 2439
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 23769
90.7%
1 2439
 
9.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23769
90.7%
1 2439
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23769
90.7%
1 2439
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23769
90.7%
1 2439
 
9.3%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23871 
1
 
2337

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Length

2025-05-15T14:15:47.899938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:47.937081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24037 
1
 
2171

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24037
91.7%
1 2171
 
8.3%

Length

2025-05-15T14:15:47.984078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.020820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24037
91.7%
1 2171
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24037
91.7%
1 2171
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24037
91.7%
1 2171
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24037
91.7%
1 2171
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24037
91.7%
1 2171
 
8.3%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23168 
1
3040 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23168
88.4%
1 3040
 
11.6%

Length

2025-05-15T14:15:48.066165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.104912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23168
88.4%
1 3040
 
11.6%

Most occurring characters

ValueCountFrequency (%)
0 23168
88.4%
1 3040
 
11.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23168
88.4%
1 3040
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23168
88.4%
1 3040
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23168
88.4%
1 3040
 
11.6%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25446 
1
 
762

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Length

2025-05-15T14:15:48.149594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.185337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring characters

ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25446
97.1%
1 762
 
2.9%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25448 
1
 
760

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25448
97.1%
1 760
 
2.9%

Length

2025-05-15T14:15:48.229673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.265472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25448
97.1%
1 760
 
2.9%

Most occurring characters

ValueCountFrequency (%)
0 25448
97.1%
1 760
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25448
97.1%
1 760
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25448
97.1%
1 760
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25448
97.1%
1 760
 
2.9%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25327 
1
 
881

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25327
96.6%
1 881
 
3.4%

Length

2025-05-15T14:15:48.308160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.345789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25327
96.6%
1 881
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25327
96.6%
1 881
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25327
96.6%
1 881
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25327
96.6%
1 881
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25327
96.6%
1 881
 
3.4%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24017 
1
 
2191

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24017
91.6%
1 2191
 
8.4%

Length

2025-05-15T14:15:48.388315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.425078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24017
91.6%
1 2191
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24017
91.6%
1 2191
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24017
91.6%
1 2191
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24017
91.6%
1 2191
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24017
91.6%
1 2191
 
8.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:48.471172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.504575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26115 
1
 
93

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26115
99.6%
1 93
 
0.4%

Length

2025-05-15T14:15:48.544009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.581971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26115
99.6%
1 93
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26115
99.6%
1 93
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26115
99.6%
1 93
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26115
99.6%
1 93
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26115
99.6%
1 93
 
0.4%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26111 
1
 
97

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Length

2025-05-15T14:15:48.624876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.660736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26111 
1
 
97

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Length

2025-05-15T14:15:48.705498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.741606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26111
99.6%
1 97
 
0.4%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26015 
1
 
193

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Length

2025-05-15T14:15:48.784366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.822072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26015
99.3%
1 193
 
0.7%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25434 
1
 
774

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Length

2025-05-15T14:15:48.865149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.901879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25434
97.0%
1 774
 
3.0%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24286 
1
 
1922

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24286
92.7%
1 1922
 
7.3%

Length

2025-05-15T14:15:48.946593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:48.982594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24286
92.7%
1 1922
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0 24286
92.7%
1 1922
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24286
92.7%
1 1922
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24286
92.7%
1 1922
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24286
92.7%
1 1922
 
7.3%

HourCounters Average Yaw Avg. [h]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23605 
1
2603 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23605
90.1%
1 2603
 
9.9%

Length

2025-05-15T14:15:49.025592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.216021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23605
90.1%
1 2603
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 23605
90.1%
1 2603
 
9.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23605
90.1%
1 2603
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23605
90.1%
1 2603
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23605
90.1%
1 2603
 
9.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26198 
1
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26198
> 99.9%
1 10
 
< 0.1%

Length

2025-05-15T14:15:49.260351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.296260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26198
> 99.9%
1 10
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26198
> 99.9%
1 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26198
> 99.9%
1 10
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26198
> 99.9%
1 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26198
> 99.9%
1 10
 
< 0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26050 
1
 
158

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26050
99.4%
1 158
 
0.6%

Length

2025-05-15T14:15:49.340286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.376184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26050
99.4%
1 158
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26050
99.4%
1 158
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26050
99.4%
1 158
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26050
99.4%
1 158
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26050
99.4%
1 158
 
0.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24485 
1
 
1723

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24485
93.4%
1 1723
 
6.6%

Length

2025-05-15T14:15:49.418736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.456629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24485
93.4%
1 1723
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 24485
93.4%
1 1723
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24485
93.4%
1 1723
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24485
93.4%
1 1723
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24485
93.4%
1 1723
 
6.6%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26027 
1
 
181

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26027
99.3%
1 181
 
0.7%

Length

2025-05-15T14:15:49.499181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.535177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26027
99.3%
1 181
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 26027
99.3%
1 181
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26027
99.3%
1 181
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26027
99.3%
1 181
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26027
99.3%
1 181
 
0.7%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:49.580072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.614273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:49.655413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.689362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:49.729106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.762609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:49.804408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.838326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:49.879954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.913904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:49.953568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:49.986982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:50.029265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.062861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:50.104317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.138047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:50.177720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.213107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:50.253245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.287043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:50.328462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.362245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24733 
1
 
1475

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24733
94.4%
1 1475
 
5.6%

Length

2025-05-15T14:15:50.402127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.439904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24733
94.4%
1 1475
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 24733
94.4%
1 1475
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24733
94.4%
1 1475
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24733
94.4%
1 1475
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24733
94.4%
1 1475
 
5.6%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25637 
1
 
571

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25637
97.8%
1 571
 
2.2%

Length

2025-05-15T14:15:50.482733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.518664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25637
97.8%
1 571
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 25637
97.8%
1 571
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25637
97.8%
1 571
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25637
97.8%
1 571
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25637
97.8%
1 571
 
2.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25142 
1
 
1066

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25142
95.9%
1 1066
 
4.1%

Length

2025-05-15T14:15:50.563402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.599530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25142
95.9%
1 1066
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25142
95.9%
1 1066
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25142
95.9%
1 1066
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25142
95.9%
1 1066
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25142
95.9%
1 1066
 
4.1%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25397 
1
 
811

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Length

2025-05-15T14:15:50.642411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.680165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25397
96.9%
1 811
 
3.1%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24538 
1
 
1670

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24538
93.6%
1 1670
 
6.4%

Length

2025-05-15T14:15:50.723201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.759130image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24538
93.6%
1 1670
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24538
93.6%
1 1670
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24538
93.6%
1 1670
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24538
93.6%
1 1670
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24538
93.6%
1 1670
 
6.4%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23822 
1
2386 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Length

2025-05-15T14:15:50.803966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.840989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23927 
1
 
2281

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23927
91.3%
1 2281
 
8.7%

Length

2025-05-15T14:15:50.886707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:50.925996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23927
91.3%
1 2281
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23927
91.3%
1 2281
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23927
91.3%
1 2281
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23927
91.3%
1 2281
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23927
91.3%
1 2281
 
8.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22088 
1
4120 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22088
84.3%
1 4120
 
15.7%

Length

2025-05-15T14:15:50.971063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.008183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22088
84.3%
1 4120
 
15.7%

Most occurring characters

ValueCountFrequency (%)
0 22088
84.3%
1 4120
 
15.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22088
84.3%
1 4120
 
15.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22088
84.3%
1 4120
 
15.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22088
84.3%
1 4120
 
15.7%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:51.055101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.088988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:51.128494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.164305image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-15T14:15:51.204468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.240815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26202 
1
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Length

2025-05-15T14:15:51.285436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.321610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26202
> 99.9%
1 6
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26125 
1
 
83

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26125
99.7%
1 83
 
0.3%

Length

2025-05-15T14:15:51.364433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.402435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26125
99.7%
1 83
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26125
99.7%
1 83
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26125
99.7%
1 83
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26125
99.7%
1 83
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26125
99.7%
1 83
 
0.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:51.445500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.479215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:15:51.520902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.554657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26069 
1
 
139

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26069
99.5%
1 139
 
0.5%

Length

2025-05-15T14:15:51.594654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:15:51.632604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26069
99.5%
1 139
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26069
99.5%
1 139
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26069
99.5%
1 139
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26069
99.5%
1 139
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26069
99.5%
1 139
 
0.5%

Correlations

2025-05-15T14:15:51.920321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0110.0100.0080.0000.0000.0000.0000.0000.0000.0140.0000.0160.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0100.0120.0000.0100.0000.0000.0000.0170.0000.0000.0000.0000.0040.0210.0210.0230.0010.0170.0000.0210.0110.0060.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0200.0140.0000.0110.0030.0040.0000.0110.0090.0000.0080.0160.0000.000
Active power limit [W]0.0001.0000.4320.0170.0000.0360.0040.0000.1940.0520.1170.0270.1170.1090.3070.0660.0040.0000.0000.0000.0000.0000.0000.0280.0490.0120.0550.0000.0000.0000.0080.0260.0340.0840.0180.0960.1050.0000.0030.0090.0660.0470.0440.0400.0000.0260.0650.0460.0680.0510.0530.0350.1240.1070.0870.0810.0740.0000.0000.0000.0100.0000.0000.0020.0000.0130.0140.5140.6030.1210.0450.7910.8470.5380.0430.7430.1730.0000.0220.0000.4320.4320.1420.0480.0100.1320.0330.0210.0740.0730.0000.0850.0220.0770.0870.0280.0000.000
Active power limit source0.0000.4321.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0810.0240.0000.0000.0000.0000.0000.0000.0250.0170.0000.0000.0000.0000.0050.0000.0000.0020.0000.0000.0000.0690.2960.0610.0190.3780.4300.2520.0330.3560.0800.0000.0080.0000.9770.9770.0040.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0040.0000.000
Ambient Temp. Avg. [°C]0.0000.0170.0061.0000.0340.0350.0140.0150.0000.0220.0270.0180.0200.0130.0000.0000.0000.0110.0120.0150.0540.0520.0240.0450.0390.0410.0100.0310.0000.0290.0000.0090.0150.0430.0310.0230.0420.0570.0500.0110.0170.0160.0100.0170.0000.0070.0000.0000.0110.0130.0000.0090.0000.0290.0160.0110.0210.0000.0110.0130.0120.0120.0040.0000.0230.0170.0140.0080.0080.0180.0300.0120.0180.0100.0050.0120.0320.0000.0000.0160.0060.0060.0250.0290.0000.0240.0000.0150.0090.0210.0000.0480.0260.0250.0230.0190.0000.006
Ambient WindDir Absolute Avg. [°]0.0000.0000.0000.0341.0000.1540.0110.0310.0000.0130.0260.0300.0150.0140.0000.0170.0150.0130.0000.0190.0060.0000.0020.0000.0030.0000.0300.0000.0000.0050.0020.0060.0030.0230.0430.0250.0250.0210.0000.0040.0270.0210.0260.0190.0000.0100.0000.0000.0090.0210.0180.0000.0100.0410.0230.0260.0320.0000.0000.0000.0050.0000.0080.0210.0000.0000.0000.0000.0000.0000.0290.0000.0000.0000.0000.0000.0150.0160.0000.0000.0000.0000.0360.0000.0050.0510.0110.0290.0160.0250.0000.0230.0320.0170.0150.0090.0000.000
Ambient WindDir Relative Avg. [°]0.0000.0360.0000.0350.1541.0000.0200.0140.0200.0020.1280.1210.0800.0710.0110.0210.0080.0000.0120.0130.0000.0250.0070.0200.0460.0220.1040.0140.0000.0070.0000.0000.0020.1090.1080.1010.0930.0280.0240.0000.0830.0060.0040.0080.0100.0050.0000.0130.0000.0070.0000.0000.0000.1130.0510.0640.0490.0150.0070.0040.0130.0000.0060.0180.0000.0000.0170.0560.0500.0130.1110.0320.0380.0510.0000.0360.0050.0130.0000.0030.0000.0000.1320.0000.0000.1450.0080.0520.0080.0810.0000.1220.0890.0760.0810.0150.0000.000
Ambient WindSpeed Avg. [m/s]0.0000.0040.0000.0140.0110.0201.0000.1470.0800.0330.1200.0370.0860.0560.0000.0030.0000.0000.0000.0130.0570.0540.0540.0520.0620.0390.0280.0110.0000.0000.0290.0300.0290.1000.0800.0800.0600.0240.0090.0460.0420.2000.1840.1840.0000.2200.0920.1110.0650.2040.0990.1130.0660.0560.0470.0440.0490.0000.0000.0000.0000.0420.0230.0190.0000.0040.0000.0150.0170.0420.0630.0140.0070.0140.0040.0140.0400.0160.0000.0000.0000.0000.0570.1160.0980.0620.0070.0150.2250.0420.0000.0970.0750.0690.0490.0150.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0000.0000.0150.0310.0140.1471.0000.0320.0650.0760.0640.0630.0540.0000.0000.0000.0060.0000.0000.0450.0280.0340.0460.0260.0170.0200.0000.0000.0000.0330.0140.0320.0590.0580.0540.0440.0120.0070.0310.0470.1110.1060.1080.0000.1270.0980.0530.0910.1000.0920.0460.0790.0520.0490.0350.0440.0000.0000.0000.0100.0000.0140.0000.0000.0000.0000.0000.0000.0340.0620.0000.0000.0000.0000.0000.0470.0140.0030.0020.0000.0000.0500.0530.0640.0460.0030.0250.1050.0380.0000.0470.0560.0400.0350.0000.0000.000
Ambient WindSpeed Min. [m/s]0.0000.1940.0000.0000.0000.0200.0800.0321.0000.0470.1260.0250.1520.1150.0930.0200.0000.0000.0130.0190.0190.0070.0170.0330.0480.0270.0280.0000.0080.0000.0190.0180.0150.0740.0510.1320.0740.0080.0110.0160.0540.0940.0980.1000.0000.0780.0360.1120.0680.0860.0380.1060.0790.1150.1020.0960.0960.0090.0000.0100.0000.0180.0240.0160.0040.0000.0050.1390.1360.0970.0760.1790.1830.1340.0000.1790.0870.0070.0080.0080.0000.0000.0920.0600.0810.0770.0170.0630.0920.0710.0000.0720.0400.1110.0560.0280.0000.000
Ambient WindSpeed StdDev [m/s]0.0000.0520.0000.0220.0130.0020.0330.0650.0471.0000.0580.0030.0570.0970.0190.0060.0020.0000.0000.0170.0250.0180.0230.0000.0380.0190.0040.0060.0050.0060.0370.0300.0290.0520.0430.0400.0890.0000.0070.0310.0510.0440.0610.0660.0000.0380.0370.0480.1370.0430.0600.0510.1490.0590.0370.0560.0470.0130.0160.0130.0170.0240.0330.0080.0000.0000.0020.0440.0470.0080.0300.0580.0600.0430.0000.0580.0200.0410.0000.0000.0000.0000.0550.0120.0200.0620.0090.0420.0440.0250.0030.0460.0330.0380.0760.0100.0000.008
Blades PitchAngle Avg. [°]0.0120.1170.0000.0270.0260.1280.1200.0760.1260.0581.0000.2740.4800.4810.0550.0280.0000.0170.0210.0250.0590.1100.0390.1160.1940.0990.0880.0190.0150.0220.0150.0150.0150.3020.2790.3060.2740.0660.0330.0480.2950.1450.1430.1690.0000.2130.2040.2230.2540.1950.1700.1630.2590.4730.3240.2630.2820.0000.0000.0000.0270.0210.0390.0160.0290.0540.0380.2080.1630.1650.4220.1130.1130.1980.0100.1260.0940.0930.0000.0110.0000.0000.3970.0960.2380.4140.0920.2720.2070.3470.0150.3300.2460.2480.2400.0440.0000.022
Blades PitchAngle Max. [°]0.0110.0270.0000.0180.0300.1210.0370.0640.0250.0030.2741.0000.1230.0880.0000.0070.0000.0000.0250.0100.0540.0420.0330.0720.0670.0410.1070.0070.0000.0140.0000.0060.0130.1320.2590.0940.0860.0430.0230.0210.2090.0930.0930.1130.0090.1550.1560.1080.1850.1240.1260.0720.1430.2050.1470.0980.0720.0000.0070.0000.0030.0070.0130.0000.0180.0340.0130.0730.0630.0200.1980.0160.0170.0690.0000.0230.1400.0440.0000.0280.0000.0000.2260.0120.1150.2630.0270.0660.1290.1530.0000.1410.2240.0930.0930.0270.0000.000
Blades PitchAngle Min. [°]0.0100.1170.0000.0200.0150.0800.0860.0630.1520.0570.4800.1231.0000.5860.0600.0300.0000.0140.0230.0290.0790.0970.0630.1090.1690.0770.0310.0280.0270.0270.0190.0110.0170.2620.1920.4070.2750.0720.0330.0300.3660.1110.1040.1270.0000.1660.1500.1900.1980.1640.1270.1480.2250.6580.5030.3870.4500.0000.0060.0000.0350.0190.0500.0220.0490.0570.0470.1940.1440.3040.5660.1130.1120.1820.0000.1260.1000.0460.0000.0140.0000.0000.4850.1820.2710.4410.1810.4630.1800.4770.0360.2800.1670.3380.2320.0530.0000.049
Blades PitchAngle StdDev [°]0.0080.1090.0000.0130.0140.0710.0560.0540.1150.0970.4810.0880.5861.0000.0480.0400.0060.0100.0320.0120.0410.0680.0280.0760.1250.0730.0470.0330.0290.0190.0020.0100.0080.2190.1830.2950.4320.0590.0340.0250.3020.1140.1110.1260.0000.1890.1740.2770.2380.1580.1310.1920.2760.5120.3850.2900.4440.0110.0010.0000.0280.0120.0440.0260.0510.0630.0610.1830.1480.2460.4380.1060.1050.1690.0260.1020.0660.1120.0000.0000.0000.0000.3540.1450.2670.3380.1570.5100.1650.3630.0350.2390.1560.2380.3680.0480.0130.066
Controller Ground Temp. Avg. [°C]0.0000.3070.0000.0000.0000.0110.0000.0000.0930.0190.0550.0000.0600.0481.0000.0530.0000.0000.0100.0010.0000.0000.0010.0000.0260.0120.0390.0000.0000.0000.0170.0060.0000.0350.0000.0450.0460.0000.0130.0000.0270.0330.0260.0220.0000.0090.0190.0120.0230.0300.0240.0000.0530.0620.0500.0360.0440.0000.0000.0000.0030.0000.0000.0000.0130.0100.0180.2240.2310.0500.0080.3110.3180.2080.0000.3050.0610.0150.0070.0040.0000.0000.0730.0230.0080.0660.0270.0080.0390.0440.0000.0430.0000.0340.0480.0000.0000.000
Controller Hub Temp. Avg. [°C]0.0000.0660.0000.0000.0170.0210.0030.0000.0200.0060.0280.0070.0300.0400.0531.0000.0000.0000.0000.0050.0000.0100.0050.0170.0180.0140.0340.0100.0210.0130.0000.0000.0100.0330.0310.0320.0310.0100.0160.0000.0140.0430.0460.0390.0000.0330.0120.0350.0280.0410.0240.0340.0320.0400.0200.0260.0430.0000.0000.0000.0000.0000.0000.0000.0180.0050.0130.0530.0540.0440.0380.0670.0650.0500.0000.0700.0080.0040.0000.0120.0000.0000.0340.0330.0290.0340.0000.0250.0420.0120.0000.0360.0210.0180.0290.0690.0000.000
Controller Top Temp. Avg. [°C]0.0000.0040.0060.0000.0150.0080.0000.0000.0000.0020.0000.0000.0000.0060.0000.0001.0000.0120.0260.0060.0130.0000.0100.0000.0000.0000.0090.0350.0130.0110.0000.0000.0000.0090.0150.0110.0170.0000.0120.0150.0060.0000.0000.0000.0000.0000.0350.0000.0010.0000.0160.0050.0040.0040.0030.0000.0000.0000.0000.0000.0000.0000.0000.0010.0100.0200.0160.0180.0070.0000.0210.0120.0080.0230.0000.0120.0050.0000.0190.0650.0060.0060.0100.0000.0020.0000.0140.0090.0000.0000.0000.0000.0080.0120.0000.0170.0000.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0000.0000.0110.0130.0000.0000.0060.0000.0000.0170.0000.0140.0100.0000.0000.0121.0000.0090.0130.0340.0240.0070.0290.0180.0280.0030.0240.0030.0130.0300.0520.0500.0100.0050.0000.0030.0000.0080.0230.0060.0000.0000.0070.0000.0000.0150.0000.0140.0000.0000.0000.0000.0020.0130.0000.0050.0000.0000.0000.0220.0220.0160.0060.0130.0090.0160.0000.0000.0170.0080.0000.0000.0000.0000.0000.0060.0140.0160.0070.0000.0000.0000.0120.0050.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.000
Controller VCP Temp. Avg. [°C]0.0000.0000.0000.0120.0000.0120.0000.0000.0130.0000.0210.0250.0230.0320.0100.0000.0260.0091.0000.0040.0020.0210.0000.0090.0180.0180.0270.0610.0430.0160.0000.0000.0000.0280.0370.0260.0360.0800.0730.0000.0200.0140.0110.0170.0000.0260.0350.0390.0250.0140.0190.0300.0140.0270.0160.0180.0300.0000.0000.0000.0000.0050.0000.0080.0520.0430.0580.0000.0000.0000.0300.0000.0000.0000.0000.0000.0190.0040.0080.0410.0000.0000.0310.0000.0290.0380.0000.0470.0200.0290.0000.0390.0330.0250.0300.0120.0000.013
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0010.0150.0190.0130.0130.0000.0190.0170.0250.0100.0290.0120.0010.0050.0060.0130.0041.0000.0240.0240.0360.0360.0410.0310.0030.0240.0160.2480.0660.0470.0650.0150.0180.0190.0180.0280.0330.1350.0290.0350.0410.0480.0050.0210.0150.0200.0200.0400.0270.0220.0230.0300.0290.0290.0170.0210.0000.0000.4190.2510.2800.0160.0000.0010.0020.0110.0000.0080.0240.0000.0000.0090.0000.0000.0060.0180.0490.0000.0010.0010.0330.0130.0130.0350.0130.0000.0330.0100.0000.0150.0230.0270.0000.0000.0070.000
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0140.0000.0000.0540.0060.0000.0570.0450.0190.0250.0590.0540.0790.0410.0000.0000.0130.0340.0020.0241.0000.2370.2440.1990.1680.1790.0330.0210.0000.0180.1130.1060.1260.1610.0870.1030.1060.0300.0110.0430.0890.0530.0530.0540.0000.0520.0450.0290.0520.0630.0460.0360.0560.0600.0630.0680.0370.0000.0000.0000.0160.0460.0350.0130.0130.0060.0090.0430.0330.0000.0600.0050.0060.0400.0000.0110.0250.0000.0100.0160.0000.0000.0980.0330.0030.0940.0000.0230.0710.0490.0000.1410.0860.1230.0990.0130.0000.016
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0000.0520.0000.0250.0540.0280.0070.0180.1100.0420.0970.0680.0000.0100.0000.0240.0210.0240.2371.0000.1320.2070.2760.3170.0430.0180.0000.0160.0840.0930.0840.2010.1170.1570.1300.0790.0460.0430.0880.0600.0590.0570.0050.0650.0680.0660.0680.0710.0690.0400.0670.0940.0690.0820.0620.0000.0000.0040.0170.0550.0340.0000.0330.0330.0250.0360.0340.0020.0980.0000.0000.0360.0000.0000.0060.0040.0140.0360.0000.0000.1290.0610.0000.1340.0000.0330.0750.0750.0030.2100.1030.1650.1390.0310.0000.012
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0160.0000.0000.0240.0020.0070.0540.0340.0170.0230.0390.0330.0630.0280.0010.0050.0100.0070.0000.0360.2440.1321.0000.1420.1330.1330.0350.0070.0200.0290.0840.0770.1020.1380.0770.0920.0940.0340.0150.0410.0600.0840.0840.0840.0100.0730.0740.0600.0610.0880.0730.0570.0780.0510.0600.0610.0300.0000.0000.0110.0180.0590.0500.0210.0000.0000.0080.0600.0380.0310.0440.0000.0000.0570.0000.0160.0510.0220.0000.0230.0000.0000.0710.0370.0440.0780.0000.0070.0910.0380.0000.1260.0830.0990.0700.0140.0000.003
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0280.0000.0450.0000.0200.0520.0460.0330.0000.1160.0720.1090.0760.0000.0170.0000.0290.0090.0360.1990.2070.1421.0000.2070.2160.0360.0340.0060.0290.0650.0740.0800.1730.1060.1400.1100.0520.0340.0340.0850.0460.0400.0410.0020.0530.0620.0480.0500.0580.0540.0320.0600.1000.0800.0760.0820.0000.0000.0000.0290.0190.0250.0000.0460.0430.0310.0650.0490.0610.1140.0290.0330.0610.0000.0330.0260.0000.0030.0350.0000.0000.1150.0980.0000.1140.0300.0330.0640.0990.0030.1730.1010.1350.1050.0300.0000.000
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0490.0000.0390.0030.0460.0620.0260.0480.0380.1940.0670.1690.1250.0260.0180.0000.0180.0180.0410.1680.2760.1330.2071.0000.2450.0800.0120.0120.0350.0850.0760.0820.2500.1630.2090.1510.0590.0340.0360.1340.0640.0650.0730.0000.0600.0560.0980.0830.0770.0590.0660.0960.1830.1200.1290.0980.0020.0060.0000.0380.0460.0470.0120.0210.0500.0150.1100.0810.0790.1720.0480.0500.1050.0000.0550.0230.0150.0030.0050.0000.0000.1980.0430.0640.2070.0200.0780.0840.1410.0000.2820.1420.1980.1280.0480.0000.017
Gear Oil TemperatureBasis Avg. [°C]0.0110.0120.0000.0410.0000.0220.0390.0170.0270.0190.0990.0410.0770.0730.0120.0140.0000.0280.0180.0310.1790.3170.1330.2160.2451.0000.0610.0210.0070.0230.0830.0780.0770.1660.1130.1410.1160.0750.0480.0220.0730.0480.0450.0440.0000.0560.0660.0620.0560.0490.0480.0520.0650.0790.0640.0720.0580.0000.0000.0000.0190.0220.0280.0000.0310.0350.0340.0380.0270.0220.0920.0080.0100.0370.0000.0110.0100.0120.0000.0270.0000.0000.1030.0210.0440.1060.0000.0540.0560.0730.0040.1810.1050.1400.1100.0390.0000.004
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0550.0000.0100.0300.1040.0280.0200.0280.0040.0880.1070.0310.0470.0390.0340.0090.0030.0270.0030.0330.0430.0350.0360.0800.0611.0000.0290.0340.0000.0060.0000.0000.0860.1280.0680.0780.0370.0270.0060.0360.0450.0430.0510.0000.0440.0540.0660.0460.0660.0500.0650.0510.0660.0230.0340.0540.0000.0000.0000.0200.0040.0000.0000.0000.0000.0200.0980.0760.0240.0320.0560.0530.0920.0030.0640.0240.0220.0130.0190.0000.0000.0700.0330.0090.1020.0340.0240.0650.0770.0120.0910.1130.0330.0830.0430.0210.004
Generator Bearing Temp. Avg. [°C]0.0000.0000.0000.0310.0000.0140.0110.0000.0000.0060.0190.0070.0280.0330.0000.0100.0350.0240.0610.0240.0210.0180.0070.0340.0120.0210.0291.0000.1000.0360.0000.0070.0120.0240.0170.0360.0260.0250.0530.0120.0000.0000.0000.0000.0000.0210.0150.0320.0040.0090.0090.0070.0150.0280.0170.0200.0290.0000.0000.0000.0200.0150.0110.0130.0480.0430.0690.0000.0100.0170.0450.0000.0000.0010.0000.0000.0000.0080.0000.0250.0000.0000.0250.0330.0150.0230.0150.0490.0120.0340.0010.0260.0170.0240.0250.0150.0110.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0000.0080.0050.0150.0000.0270.0290.0000.0210.0130.0030.0430.0160.0000.0000.0200.0060.0120.0070.0340.1001.0000.0260.0140.0040.0000.0200.0220.0300.0300.0330.0230.0180.0000.0250.0210.0210.0000.0270.0260.0260.0210.0320.0250.0300.0270.0350.0200.0230.0360.0150.0060.0000.0080.0000.0130.0000.0400.0520.0500.0110.0000.0180.0300.0000.0000.0120.0000.0140.0020.0190.0130.0190.0000.0000.0240.0220.0300.0260.0050.0460.0320.0290.0000.0200.0160.0200.0230.0140.0000.005
Generator CoolingWater Temp. Avg. [°C]0.0000.0000.0000.0290.0050.0070.0000.0000.0000.0060.0220.0140.0270.0190.0000.0130.0110.0130.0160.2480.0180.0160.0290.0290.0350.0230.0000.0360.0261.0000.0380.0260.0500.0360.0060.0420.0170.0320.0380.0940.0270.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0290.0180.0280.0000.0000.0000.0090.2680.1410.1850.0200.0160.0150.0140.0080.0000.0000.0350.0000.0000.0050.0000.0000.0360.0070.0310.0120.0000.0000.0370.0030.0060.0330.0160.0080.0000.0080.0060.0340.0120.0570.0100.0000.0000.000
Generator Phase1 Temp. Avg. [°C]0.0000.0080.0000.0000.0020.0000.0290.0330.0190.0370.0150.0000.0190.0020.0170.0000.0000.0300.0000.0660.1130.0840.0840.0650.0850.0830.0060.0000.0140.0381.0000.4470.3660.0390.0260.0280.0400.0170.0040.0660.0570.0680.0830.0860.0000.0330.0160.0190.0320.0630.0540.0530.0320.0350.0270.0580.0160.0000.0000.0000.0690.0830.0710.0210.0190.0230.0250.0370.0220.0080.0120.0150.0120.0340.0000.0080.0080.0170.0000.0000.0000.0000.0510.0000.0040.0590.0370.0010.0580.0000.0000.0400.0230.0410.0240.0000.0000.000
Generator Phase2 Temp. Avg. [°C]0.0000.0260.0000.0090.0060.0000.0300.0140.0180.0300.0150.0060.0110.0100.0060.0000.0000.0520.0000.0470.1060.0930.0770.0740.0760.0780.0000.0070.0040.0260.4471.0000.3730.0360.0320.0230.0250.0000.0140.0520.0370.0540.0730.0720.0000.0200.0130.0100.0300.0470.0560.0360.0290.0280.0300.0500.0000.0060.0000.0000.0530.0660.0590.0110.0080.0100.0130.0310.0140.0010.0000.0000.0000.0280.0000.0060.0000.0050.0000.0030.0000.0000.0400.0000.0000.0490.0360.0040.0500.0000.0000.0400.0250.0260.0240.0000.0000.000
Generator Phase3 Temp. Avg. [°C]0.0000.0340.0000.0150.0030.0020.0290.0320.0150.0290.0150.0130.0170.0080.0000.0100.0000.0500.0000.0650.1260.0840.1020.0800.0820.0770.0000.0120.0000.0500.3660.3731.0000.0350.0330.0120.0380.0180.0220.0600.0360.0590.0740.0820.0020.0310.0100.0130.0350.0610.0490.0450.0320.0240.0190.0550.0000.0090.0030.0060.0520.0760.0740.0080.0220.0180.0350.0300.0160.0110.0000.0100.0110.0280.0000.0100.0210.0220.0060.0070.0000.0000.0370.0000.0090.0430.0370.0140.0580.0000.0040.0360.0230.0320.0300.0000.0000.011
Generator RPM Avg. [RPM]0.0100.0840.0000.0430.0230.1090.1000.0590.0740.0520.3020.1320.2620.2190.0350.0330.0090.0100.0280.0150.1610.2010.1380.1730.2500.1660.0860.0240.0200.0360.0390.0360.0351.0000.4350.3990.4980.0780.0240.0050.2150.1340.1180.1270.0000.1410.1590.1610.1990.1460.1440.1010.2070.2670.1560.1890.1450.0000.0000.0000.0190.0240.0270.0150.0210.0300.0300.1670.1390.0460.2560.0790.0860.1600.0080.0900.0290.0460.0000.0270.0000.0000.3260.0430.0790.3470.0000.1430.1560.2010.0390.7530.4060.3510.4390.0700.0000.041
Generator RPM Max. [RPM]0.0120.0180.0000.0310.0430.1080.0800.0580.0510.0430.2790.2590.1920.1830.0000.0310.0150.0050.0370.0180.0870.1170.0770.1060.1630.1130.1280.0170.0220.0060.0260.0320.0330.4351.0000.2030.3570.0670.0390.0250.1740.1190.1160.1280.0000.1350.1650.1640.1980.1220.1500.1090.1750.2430.1540.1270.1320.0000.0000.0000.0100.0150.0210.0150.0210.0260.0230.0820.0670.0740.2370.0200.0180.0760.0000.0290.0060.0530.0000.0070.0000.0000.2200.0050.1630.2680.0230.1650.1280.1690.0040.3880.7540.1750.2970.0790.0000.013
Generator RPM Min. [RPM]0.0000.0960.0000.0230.0250.1010.0800.0540.1320.0400.3060.0940.4070.2950.0450.0320.0110.0000.0260.0190.1030.1570.0920.1400.2090.1410.0680.0360.0300.0420.0280.0230.0120.3990.2031.0000.3200.0940.0560.0160.2810.1100.0970.1100.0000.1180.0880.1720.1000.1500.0760.1510.1270.3680.2640.2980.2540.0030.0170.0000.0330.0190.0260.0210.0370.0360.0390.1680.1260.2190.4450.0960.0990.1610.0000.1080.0880.0370.0050.0130.0000.0000.4210.1700.1630.3850.0290.2780.1580.2790.0450.4140.1900.7510.2670.0510.0040.066
Generator RPM StdDev [RPM]0.0100.1050.0000.0420.0250.0930.0600.0440.0740.0890.2740.0860.2750.4320.0460.0310.0170.0030.0360.0180.1060.1300.0940.1100.1510.1160.0780.0260.0300.0170.0400.0250.0380.4980.3570.3201.0000.0790.0270.0210.2600.1180.1210.1240.0000.1510.1660.2660.2270.1330.1470.2030.2590.2500.1610.1870.2510.0040.0000.0000.0210.0220.0300.0170.0220.0390.0460.1800.1410.0270.2470.0920.0970.1700.0160.0900.0460.1100.0000.0240.0000.0000.3040.0180.1130.3110.0120.3020.1310.1610.0400.4760.3140.2680.7130.0620.0150.053
Generator SlipRing Temp. Avg. [°C]0.0000.0000.0020.0570.0210.0280.0240.0120.0080.0000.0660.0430.0720.0590.0000.0100.0000.0000.0800.0280.0300.0790.0340.0520.0590.0750.0370.0250.0330.0320.0170.0000.0180.0780.0670.0940.0791.0000.0760.0070.0710.0330.0270.0400.0110.0540.0460.0660.0620.0550.0460.0520.0550.0740.0590.0490.0560.0040.0050.0000.0190.0090.0200.0200.0270.0280.0380.0020.0000.0130.0890.0000.0050.0070.0100.0000.0240.0140.0030.0490.0020.0020.0900.0230.0510.0940.0060.0670.0520.0600.0000.0830.0540.0810.0690.0300.0070.003
Grid Busbar Temp. Avg. [°C]0.0000.0030.0000.0500.0000.0240.0090.0070.0110.0070.0330.0230.0330.0340.0130.0160.0120.0080.0730.0330.0110.0460.0150.0340.0340.0480.0270.0530.0230.0380.0040.0140.0220.0240.0390.0560.0270.0761.0000.0050.0400.0180.0180.0220.0090.0360.0240.0360.0250.0350.0200.0300.0090.0420.0280.0330.0360.0000.0000.0050.0390.0210.0180.0330.0490.0510.0440.0000.0000.0270.0530.0020.0000.0000.0000.0020.0210.0280.0000.0510.0000.0000.0380.0250.0380.0400.0050.0470.0330.0220.0000.0330.0250.0490.0200.0240.0000.017
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0090.0000.0110.0040.0000.0460.0310.0160.0310.0480.0210.0300.0250.0000.0000.0150.0230.0000.1350.0430.0430.0410.0340.0360.0220.0060.0120.0180.0940.0660.0520.0600.0050.0250.0160.0210.0070.0051.0000.0410.0810.0870.0980.0000.0650.0410.0440.0440.0830.0630.0630.0480.0350.0330.0440.0320.0040.0000.0000.1340.3120.2500.0050.0050.0090.0110.0430.0360.0110.0160.0000.0070.0350.0000.0000.0150.0180.0310.0210.0000.0000.0470.0310.0270.0450.0060.0000.0830.0150.0000.0000.0220.0160.0090.0150.0000.013
Grid Production CosPhi Avg.0.0170.0660.0000.0170.0270.0830.0420.0470.0540.0510.2950.2090.3660.3020.0270.0140.0060.0060.0200.0290.0890.0880.0600.0850.1340.0730.0360.0000.0000.0270.0570.0370.0360.2150.1740.2810.2600.0710.0400.0411.0000.1570.1780.2110.0010.1970.1900.2120.2050.2140.2250.1710.2240.4650.3270.2990.3140.0000.0030.0000.0400.0380.0440.0120.0030.0470.0130.1290.1100.0000.4830.0620.0640.1230.0000.0680.1130.1030.0000.0130.0000.0000.5820.0000.1820.5670.0590.3720.2230.3230.0540.2300.1490.2180.2230.0420.0350.065
Grid Production CurrentPhase1 Avg. [A]0.0000.0470.0000.0160.0210.0060.2000.1110.0940.0440.1450.0930.1110.1140.0330.0430.0000.0000.0140.0350.0530.0600.0840.0460.0640.0480.0450.0000.0250.0000.0680.0540.0590.1340.1190.1100.1180.0330.0180.0810.1571.0000.6800.6410.0000.5110.2310.2760.2520.6430.2960.3740.2910.1760.1260.1260.1330.0000.0160.0050.0310.0690.0630.0180.0100.0050.0100.1490.1510.0840.1230.0560.0480.1460.0210.0630.1680.0950.0020.0170.0000.0000.2340.1970.3180.2080.0000.0690.6150.1160.0000.1330.1020.0810.1040.0250.0000.000
Grid Production CurrentPhase2 Avg. [A]0.0000.0440.0000.0100.0260.0040.1840.1060.0980.0610.1430.0930.1040.1110.0260.0460.0000.0000.0110.0410.0530.0590.0840.0400.0650.0450.0430.0000.0210.0000.0830.0730.0740.1180.1160.0970.1210.0270.0180.0870.1780.6801.0000.7190.0000.5000.2350.2720.2490.5730.3070.3410.3020.2030.1330.1610.1670.0040.0210.0070.0350.0710.0640.0190.0000.0000.0040.1350.1350.0690.1270.0490.0440.1320.0080.0550.1360.1030.0140.0170.0000.0000.2040.1700.3220.2440.0000.0640.5580.1330.0000.1190.0970.0670.1090.0260.0000.000
Grid Production CurrentPhase3 Avg. [A]0.0000.0400.0000.0170.0190.0080.1840.1080.1000.0660.1690.1130.1270.1260.0220.0390.0000.0070.0170.0480.0540.0570.0840.0410.0730.0440.0510.0000.0210.0000.0860.0720.0820.1270.1280.1100.1240.0400.0220.0980.2110.6410.7191.0000.0000.5350.2630.2870.2780.6350.3390.3640.3170.2320.1410.1630.1790.0000.0090.0000.0410.0800.0680.0160.0000.0000.0000.1420.1370.0750.1570.0480.0430.1380.0080.0600.1080.1080.0060.0300.0000.0000.2360.1780.3550.2660.0000.0760.6120.1490.0080.1310.1030.0770.1150.0250.0140.010
Grid Production Frequency Avg. [Hz]0.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0050.0000.0050.0100.0020.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0110.0090.0000.0010.0000.0000.0001.0000.0000.0040.0000.0000.0000.0000.0000.0000.0040.0090.0060.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0020.0000.0280.0000.0000.0000.0030.0000.0000.0060.0000.0060.0000.0000.0000.0000.0000.0000.0000.0030.0000.000
Grid Production PossiblePower Avg. [W]0.0040.0260.0000.0070.0100.0050.2200.1270.0780.0380.2130.1550.1660.1890.0090.0330.0000.0000.0260.0210.0520.0650.0730.0530.0600.0560.0440.0210.0270.0000.0330.0200.0310.1410.1350.1180.1510.0540.0360.0650.1970.5110.5000.5350.0001.0000.3730.4160.4210.6630.2940.3280.3730.1580.1490.0970.1390.0000.0000.0000.0180.0470.0470.0010.0060.0240.0080.1150.1070.0730.2140.0300.0270.1110.0000.0300.1090.1070.0000.0460.0000.0000.1930.2600.4370.1750.0490.1270.6490.1300.0040.1430.1210.0920.1350.0180.0000.004
Grid Production PossiblePower Max. [W]0.0210.0650.0810.0000.0000.0000.0920.0980.0360.0370.2040.1560.1500.1740.0190.0120.0350.0150.0350.0150.0450.0680.0740.0620.0560.0660.0540.0150.0260.0020.0160.0130.0100.1590.1650.0880.1660.0460.0240.0410.1900.2310.2350.2630.0040.3731.0000.2690.4060.2970.6600.1930.3300.1600.1520.0670.1410.0000.0000.0110.0190.0330.0290.0000.0000.0140.0000.0860.1130.0490.1940.0690.0640.1060.0100.0650.0420.0660.0090.0400.0810.0810.1710.0820.2450.1810.0460.1190.3060.1470.0000.1550.1420.0650.1700.0190.0000.004
Grid Production PossiblePower Min. [W]0.0210.0460.0240.0000.0000.0130.1110.0530.1120.0480.2230.1080.1900.2770.0120.0350.0000.0000.0390.0200.0290.0660.0600.0480.0980.0620.0660.0320.0260.0000.0190.0100.0130.1610.1640.1720.2660.0660.0360.0440.2120.2760.2720.2870.0000.4160.2691.0000.3010.3310.2340.5210.3170.1690.1270.0900.1940.0110.0000.0000.0260.0350.0430.0020.0130.0420.0400.0750.0900.0740.2110.0480.0490.0860.0000.0440.0760.1020.0000.0200.0240.0240.1900.1130.2820.1860.0110.2740.3430.1180.0210.1680.1390.1400.2290.0270.0290.018
Grid Production PossiblePower StdDev [W]0.0230.0680.0000.0110.0090.0000.0650.0910.0680.1370.2540.1850.1980.2380.0230.0280.0010.0140.0250.0200.0520.0680.0610.0500.0830.0560.0460.0040.0210.0000.0320.0300.0350.1990.1980.1000.2270.0620.0250.0440.2050.2520.2490.2780.0000.4210.4060.3011.0000.3130.3050.2210.7320.2210.2000.1040.1500.0000.0000.0030.0220.0300.0330.0000.0220.0160.0040.1200.1270.0710.2310.0710.0690.1200.0000.0710.0700.1110.0000.0270.0000.0000.2140.0940.2800.2250.0500.1540.3240.1710.0000.1960.1760.0890.2070.0230.0000.000
Grid Production Power Avg. [W]0.0010.0510.0000.0130.0210.0070.2040.1000.0860.0430.1950.1240.1640.1580.0300.0410.0000.0000.0140.0400.0630.0710.0880.0580.0770.0490.0660.0090.0320.0000.0630.0470.0610.1460.1220.1500.1330.0550.0350.0830.2140.6430.5730.6350.0000.6630.2970.3310.3131.0000.3550.4010.3600.2010.1530.1410.1490.0000.0050.0000.0290.0650.0630.0210.0140.0120.0000.1610.1580.0920.1930.0570.0510.1570.0110.0640.1080.1010.0030.0370.0000.0000.3180.2680.4220.2380.0300.1090.8570.1530.0000.1470.1080.1180.1220.0210.0000.000
Grid Production Power Max. [W]0.0170.0530.0000.0000.0180.0000.0990.0920.0380.0600.1700.1260.1270.1310.0240.0240.0160.0000.0190.0270.0460.0690.0730.0540.0590.0480.0500.0090.0250.0000.0540.0560.0490.1440.1500.0760.1470.0460.0200.0630.2250.2960.3070.3390.0000.2940.6600.2340.3050.3551.0000.2230.3300.1800.1700.0860.1200.0000.0000.0100.0240.0410.0440.0140.0000.0130.0000.0980.0930.0330.1690.0530.0520.0830.0060.0530.0210.0550.0180.0320.0000.0000.2010.0700.2260.2230.0090.0850.3490.1430.0000.1420.1310.0470.1520.0240.0000.009
Grid Production Power Min. [W]0.0000.0350.0000.0090.0000.0000.1130.0460.1060.0510.1630.0720.1480.1920.0000.0340.0050.0000.0300.0220.0360.0400.0570.0320.0660.0520.0650.0070.0300.0000.0530.0360.0450.1010.1090.1510.2030.0520.0300.0630.1710.3740.3410.3640.0000.3280.1930.5210.2210.4010.2231.0000.2670.1560.1100.1470.1630.0000.0040.0000.0260.0500.0440.0140.0080.0270.0260.0810.0820.0520.1460.0430.0390.0830.0060.0350.0670.1280.0000.0210.0000.0000.1890.0850.2710.1760.0020.1820.3850.0970.0060.1030.0930.1160.1720.0320.0000.000
Grid Production Power StdDev [W]0.0210.1240.0000.0000.0100.0000.0660.0790.0790.1490.2590.1430.2250.2760.0530.0320.0040.0000.0140.0230.0560.0670.0780.0600.0960.0650.0510.0150.0270.0000.0320.0290.0320.2070.1750.1270.2590.0550.0090.0480.2240.2910.3020.3170.0000.3730.3300.3170.7320.3600.3300.2671.0000.2580.2070.1290.1950.0000.0000.0000.0210.0320.0370.0060.0260.0140.0080.2240.2010.1170.2260.1250.1180.2180.0210.1280.0920.1130.0000.0330.0000.0000.2550.1160.2890.2580.0910.1720.3710.1990.0000.2100.1530.1100.2350.0310.0160.000
Grid Production ReactivePower Avg. [W]0.0110.1070.0000.0290.0410.1130.0560.0520.1150.0590.4730.2050.6580.5120.0620.0400.0040.0020.0270.0300.0600.0940.0510.1000.1830.0790.0660.0280.0350.0290.0350.0280.0240.2670.2430.3680.2500.0740.0420.0350.4650.1760.2030.2320.0040.1580.1600.1690.2210.2010.1800.1560.2581.0000.6150.4750.5410.0000.0140.0000.0380.0230.0510.0260.0530.0590.0440.1950.1590.3290.6610.1070.1050.1870.0000.1200.0920.0930.0050.0190.0000.0000.6260.1740.2900.7200.1780.5340.1990.6830.0490.2840.2090.2860.2090.0610.0000.066
Grid Production ReactivePower Max. [W]0.0060.0870.0250.0160.0230.0510.0470.0490.1020.0370.3240.1470.5030.3850.0500.0200.0030.0130.0160.0290.0630.0690.0600.0800.1200.0640.0230.0170.0200.0180.0270.0300.0190.1560.1540.2640.1610.0590.0280.0330.3270.1260.1330.1410.0090.1490.1520.1270.2000.1530.1700.1100.2070.6151.0000.3770.4310.0040.0160.0080.0330.0170.0420.0160.0320.0290.0200.1440.1180.2580.4750.0820.0830.1360.0110.0860.1020.1160.0070.0140.0250.0250.4070.1410.2480.4170.2030.3780.1550.4810.0220.1660.1340.2080.1240.0480.0000.035
Grid Production ReactivePower Min. [W]0.0000.0810.0170.0110.0260.0640.0440.0350.0960.0560.2630.0980.3870.2900.0360.0260.0000.0000.0180.0290.0680.0820.0610.0760.1290.0720.0340.0200.0230.0280.0580.0500.0550.1890.1270.2980.1870.0490.0330.0440.2990.1260.1610.1630.0060.0970.0670.0900.1040.1410.0860.1470.1290.4750.3771.0000.3470.0000.0170.0000.0370.0450.0440.0070.0310.0330.0240.1480.1110.1620.3660.0780.0780.1390.0000.0850.1030.2230.0130.0080.0170.0170.3940.0930.1490.4040.0570.3260.1380.3350.0430.1990.1100.2530.1560.0520.0190.051
Grid Production ReactivePower StdDev [W]0.0010.0740.0000.0210.0320.0490.0490.0440.0960.0470.2820.0720.4500.4440.0440.0430.0000.0050.0300.0170.0370.0620.0300.0820.0980.0580.0540.0290.0360.0000.0160.0000.0000.1450.1320.2540.2510.0560.0360.0320.3140.1330.1670.1790.0000.1390.1410.1940.1500.1490.1200.1630.1950.5410.4310.3471.0000.0100.0110.0060.0160.0160.0400.0150.0220.0490.0320.1370.1050.2660.4520.0720.0730.1270.0000.0770.0210.1200.0260.0270.0000.0000.3760.1660.2200.3800.1830.4700.1400.4290.0290.1500.1130.1740.2250.0470.0000.059
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0000.0000.0150.0000.0000.0090.0130.0000.0000.0000.0110.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0020.0000.0000.0000.0150.0000.0000.0060.0090.0000.0000.0030.0040.0040.0000.0040.0000.0000.0040.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0040.0000.0101.0000.5530.5960.0000.0000.0180.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0120.0000.0000.0000.0000.0050.0000.0000.003
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0000.0110.0000.0070.0000.0000.0000.0160.0000.0070.0060.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0060.0000.0000.0000.0030.0000.0000.0170.0000.0050.0000.0000.0030.0160.0210.0090.0070.0000.0000.0000.0000.0050.0000.0040.0000.0140.0160.0170.0110.5531.0000.5620.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0070.0020.0000.0200.0160.0000.0000.0260.0000.0000.0150.0120.0000.0000.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0000.0130.0000.0040.0000.0000.0100.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0110.0000.0000.0000.0000.0000.0000.0090.0000.0000.0060.0000.0000.0000.0000.0000.0050.0000.0000.0050.0070.0000.0000.0000.0110.0000.0030.0000.0100.0000.0000.0000.0080.0000.0060.5960.5621.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0020.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0170.0000.0000.0090.0000.0000.0000.0000.0020.0000.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0100.0050.0120.0050.0130.0000.0100.0000.0170.0270.0030.0350.0280.0030.0000.0000.0220.0000.4190.0160.0170.0180.0290.0380.0190.0200.0200.0080.2680.0690.0530.0520.0190.0100.0330.0210.0190.0390.1340.0400.0310.0350.0410.0000.0180.0190.0260.0220.0290.0240.0260.0210.0380.0330.0370.0160.0000.0000.0061.0000.2370.2560.0150.0120.0200.0030.0000.0000.0150.0360.0080.0070.0000.0000.0080.0060.0100.0490.0010.0050.0050.0360.0140.0070.0400.0110.0230.0230.0200.0000.0180.0080.0410.0100.0040.0000.000
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0000.0120.0000.0000.0420.0000.0180.0240.0210.0070.0190.0120.0000.0000.0000.0220.0050.2510.0460.0550.0590.0190.0460.0220.0040.0150.0000.1410.0830.0660.0760.0240.0150.0190.0220.0090.0210.3120.0380.0690.0710.0800.0000.0470.0330.0350.0300.0650.0410.0500.0320.0230.0170.0450.0160.0000.0000.0000.2371.0000.3420.0040.0110.0000.0000.0340.0220.0000.0130.0000.0000.0260.0000.0000.0170.0180.0460.0120.0000.0000.0400.0250.0160.0420.0230.0030.0660.0000.0000.0280.0230.0300.0040.0080.0090.008
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0000.0000.0040.0080.0060.0230.0140.0240.0330.0390.0130.0500.0440.0000.0000.0000.0160.0000.2800.0350.0340.0500.0250.0470.0280.0000.0110.0130.1850.0710.0590.0740.0270.0210.0260.0300.0200.0180.2500.0440.0630.0640.0680.0000.0470.0290.0430.0330.0630.0440.0440.0370.0510.0420.0440.0400.0180.0000.0000.2560.3421.0000.0150.0200.0050.0100.0230.0150.0120.0360.0000.0000.0220.0000.0000.0170.0320.0420.0130.0000.0000.0520.0330.0210.0550.0100.0210.0620.0270.0000.0240.0250.0280.0200.0090.0000.000
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0020.0020.0000.0210.0180.0190.0000.0160.0080.0160.0000.0220.0260.0000.0000.0010.0060.0080.0160.0130.0000.0210.0000.0120.0000.0000.0130.0000.0200.0210.0110.0080.0150.0150.0210.0170.0200.0330.0050.0120.0180.0190.0160.0000.0010.0000.0020.0000.0210.0140.0140.0060.0260.0160.0070.0150.0000.0000.0000.0150.0040.0151.0000.0200.0000.0160.0090.0000.0120.0220.0000.0000.0030.0000.0000.0000.0040.0000.0310.0020.0020.0180.0060.0170.0180.0100.0160.0180.0050.0000.0080.0140.0220.0060.0100.0000.000
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0000.0230.0000.0000.0000.0000.0040.0000.0290.0180.0490.0510.0130.0180.0100.0130.0520.0000.0130.0330.0000.0460.0210.0310.0000.0480.0400.0160.0190.0080.0220.0210.0210.0370.0220.0270.0490.0050.0030.0100.0000.0000.0000.0060.0000.0130.0220.0140.0000.0080.0260.0530.0320.0310.0220.0000.0000.0000.0120.0110.0200.0201.0000.1530.3390.0130.0000.0490.0520.0000.0000.0140.0000.0080.0210.0170.0000.0110.0000.0000.0230.0400.0310.0240.0020.0420.0080.0340.0000.0290.0100.0360.0190.0300.0000.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0130.0000.0170.0000.0000.0040.0000.0000.0000.0540.0340.0570.0630.0100.0050.0200.0090.0430.0010.0060.0330.0000.0430.0500.0350.0000.0430.0520.0150.0230.0100.0180.0300.0260.0360.0390.0280.0510.0090.0470.0050.0000.0000.0000.0240.0140.0420.0160.0120.0130.0270.0140.0590.0290.0330.0490.0000.0000.0000.0200.0000.0050.0000.1531.0000.1360.0190.0060.0430.0740.0160.0130.0200.0000.0010.0390.0130.0060.0000.0000.0000.0470.0270.0380.0480.0000.0770.0190.0380.0000.0280.0140.0370.0320.0000.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0140.0000.0140.0000.0170.0000.0000.0050.0020.0380.0130.0470.0610.0180.0130.0160.0160.0580.0020.0090.0250.0080.0310.0150.0340.0200.0690.0500.0140.0250.0130.0350.0300.0230.0390.0460.0380.0440.0110.0130.0100.0040.0000.0000.0080.0000.0400.0040.0000.0000.0260.0080.0440.0200.0240.0320.0000.0050.0000.0030.0000.0100.0160.3390.1361.0000.0310.0130.0290.0490.0000.0100.0210.0000.0050.0320.0140.0000.0170.0000.0000.0350.0330.0130.0270.0040.0590.0040.0220.0130.0280.0110.0280.0340.0120.0170.000
HourCounters Average AlarmActive Avg. [h]0.0000.5140.0690.0080.0000.0560.0150.0000.1390.0440.2080.0730.1940.1830.2240.0530.0180.0000.0000.0110.0430.0360.0600.0650.1100.0380.0980.0000.0110.0080.0370.0310.0300.1670.0820.1680.1800.0020.0000.0430.1290.1490.1350.1420.0000.1150.0860.0750.1200.1610.0980.0810.2240.1950.1440.1480.1370.0000.0000.0000.0000.0340.0230.0090.0130.0190.0311.0000.7460.2400.0480.5070.5100.9120.1520.5370.2000.0250.0170.0070.0690.0690.2520.1720.0000.2380.0940.0270.1780.1370.0000.1740.0650.1390.1530.0290.0000.000
HourCounters Average AmbientOk Avg. [h]0.0000.6030.2960.0080.0000.0500.0170.0000.1360.0470.1630.0630.1440.1480.2310.0540.0070.0000.0000.0000.0330.0340.0380.0490.0810.0270.0760.0100.0000.0000.0220.0140.0160.1390.0670.1260.1410.0000.0000.0360.1100.1510.1350.1370.0000.1070.1130.0900.1270.1580.0930.0820.2010.1590.1180.1110.1050.0000.0000.0000.0000.0220.0150.0000.0000.0060.0130.7461.0000.2320.0390.7620.7120.8260.1880.7050.2270.0250.0210.0000.2960.2960.2000.1660.0000.1920.0820.0100.1750.1090.0000.1490.0540.1030.1220.0270.0000.000
HourCounters Average Gen1 Avg. [h]0.0000.1210.0610.0180.0000.0130.0420.0340.0970.0080.1650.0200.3040.2460.0500.0440.0000.0170.0000.0080.0000.0020.0310.0610.0790.0220.0240.0170.0180.0000.0080.0010.0110.0460.0740.2190.0270.0130.0270.0110.0000.0840.0690.0750.0000.0730.0490.0740.0710.0920.0330.0520.1170.3290.2580.1620.2660.0000.0000.0060.0150.0000.0120.0120.0490.0430.0290.2400.2321.0000.4840.1360.1280.2580.0250.1510.0380.0030.0000.0070.0610.0610.0560.5970.3710.0460.2640.1760.0980.2520.0050.0600.0520.1820.0150.0140.0000.000
HourCounters Average Gen2 Avg. [h]0.0130.0450.0190.0300.0290.1110.0630.0620.0760.0300.4220.1980.5660.4380.0080.0380.0210.0080.0300.0240.0600.0980.0440.1140.1720.0920.0320.0450.0300.0350.0120.0000.0000.2560.2370.4450.2470.0890.0530.0160.4830.1230.1270.1570.0080.2140.1940.2110.2310.1930.1690.1460.2260.6610.4750.3660.4520.0040.0090.0000.0360.0130.0360.0220.0520.0740.0490.0480.0390.4841.0000.0460.0480.0580.0000.0460.0710.0740.0040.0140.0190.0190.6510.2470.4870.5820.0720.5040.2040.4850.0530.2750.2030.3580.2040.0480.0000.081
HourCounters Average GridOk Avg. [h]0.0000.7910.3780.0120.0000.0320.0140.0000.1790.0580.1130.0160.1130.1060.3110.0670.0120.0000.0000.0000.0050.0000.0000.0290.0480.0080.0560.0000.0000.0000.0150.0000.0100.0790.0200.0960.0920.0000.0020.0000.0620.0560.0490.0480.0000.0300.0690.0480.0710.0570.0530.0430.1250.1070.0820.0780.0720.0000.0000.0000.0080.0000.0000.0000.0000.0160.0000.5070.7620.1360.0461.0000.9320.6080.2400.9220.1800.0050.0250.0000.3780.3780.1420.0530.0090.1340.0310.0190.0810.0760.0000.0830.0170.0770.0810.0330.0000.000
HourCounters Average GridOn Avg. [h]0.0000.8470.4300.0180.0000.0380.0070.0000.1830.0600.1130.0170.1120.1050.3180.0650.0080.0000.0000.0000.0060.0000.0000.0330.0500.0100.0530.0000.0000.0000.0120.0000.0110.0860.0180.0990.0970.0050.0000.0070.0640.0480.0440.0430.0000.0270.0640.0490.0690.0510.0520.0390.1180.1050.0830.0780.0730.0000.0000.0000.0070.0000.0000.0000.0000.0130.0100.5100.7120.1280.0480.9321.0000.5840.0480.8790.1900.0000.0260.0000.4300.4300.1450.0540.0060.1330.0330.0160.0840.0750.0000.0860.0200.0800.0780.0340.0000.000
HourCounters Average Run Avg. [h]0.0000.5380.2520.0100.0000.0510.0140.0000.1340.0430.1980.0690.1820.1690.2080.0500.0230.0000.0000.0090.0400.0360.0570.0610.1050.0370.0920.0010.0120.0050.0340.0280.0280.1600.0760.1610.1700.0070.0000.0350.1230.1460.1320.1380.0000.1110.1060.0860.1200.1570.0830.0830.2180.1870.1360.1390.1270.0000.0000.0020.0000.0260.0220.0030.0140.0200.0210.9120.8260.2580.0580.6080.5841.0000.1010.6380.2170.0240.0220.0080.2520.2520.2370.1720.0000.2250.0930.0270.1640.1290.0000.1680.0560.1330.1480.0280.0000.000
HourCounters Average ServiceOn Avg. [h]0.0000.0430.0330.0050.0000.0000.0040.0000.0000.0000.0100.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0080.0000.0000.0160.0100.0000.0000.0000.0210.0080.0080.0000.0000.0100.0000.0000.0110.0060.0060.0210.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.1520.1880.0250.0000.2400.0480.1011.0000.1760.0020.0080.0000.0000.0330.0330.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0070.0000.0050.0000.0000.000
HourCounters Average TurbineOk Avg. [h]0.0000.7430.3560.0120.0000.0360.0140.0000.1790.0580.1260.0230.1260.1020.3050.0700.0120.0000.0000.0000.0110.0000.0160.0330.0550.0110.0640.0000.0140.0000.0080.0060.0100.0900.0290.1080.0900.0000.0020.0000.0680.0630.0550.0600.0000.0300.0650.0440.0710.0640.0530.0350.1280.1200.0860.0850.0770.0000.0000.0000.0080.0000.0000.0000.0080.0010.0050.5370.7050.1510.0460.9220.8790.6380.1761.0000.1750.0000.0250.0000.3560.3560.1580.0660.0000.1500.0310.0070.0920.0870.0000.0920.0270.0880.0770.0380.0000.000
HourCounters Average WindOk Avg. [h]0.0000.1730.0800.0320.0150.0050.0400.0470.0870.0200.0940.1400.1000.0660.0610.0080.0050.0060.0190.0060.0250.0060.0510.0260.0230.0100.0240.0000.0020.0360.0080.0000.0210.0290.0060.0880.0460.0240.0210.0150.1130.1680.1360.1080.0020.1090.0420.0760.0700.1080.0210.0670.0920.0920.1020.1030.0210.0000.0000.0000.0060.0170.0170.0000.0210.0390.0320.2000.2270.0380.0710.1800.1900.2170.0020.1751.0000.0570.0060.0000.0800.0800.1580.0170.0870.1380.0460.0610.1180.0260.0000.0280.0000.1010.0210.0240.0000.007
HourCounters Average Yaw Avg. [h]0.0000.0000.0000.0000.0160.0130.0160.0140.0070.0410.0930.0440.0460.1120.0150.0040.0000.0140.0040.0180.0000.0040.0220.0000.0150.0120.0220.0080.0190.0070.0170.0050.0220.0460.0530.0370.1100.0140.0280.0180.1030.0950.1030.1080.0000.1070.0660.1020.1110.1010.0550.1280.1130.0930.1160.2230.1200.0000.0000.0000.0100.0180.0320.0040.0170.0130.0140.0250.0250.0030.0740.0050.0000.0240.0080.0000.0571.0000.0000.0000.0000.0000.0880.0090.0980.1070.0140.1050.0980.0590.0010.0440.0560.0390.0870.0000.0240.008
Hydraulic Oil Temp. Avg. [°C]0.0000.0220.0080.0000.0000.0000.0000.0030.0080.0000.0000.0000.0000.0000.0070.0000.0190.0160.0080.0490.0100.0140.0000.0030.0030.0000.0130.0000.0130.0310.0000.0000.0060.0000.0000.0050.0000.0030.0000.0310.0000.0020.0140.0060.0280.0000.0090.0000.0000.0030.0180.0000.0000.0050.0070.0130.0260.0080.0000.0000.0490.0460.0420.0000.0000.0060.0000.0170.0210.0000.0040.0250.0260.0220.0000.0250.0060.0001.0000.0310.0080.0080.0000.0070.0120.0000.0210.0020.0040.0190.0000.0130.0000.0100.0200.0000.0000.000
Nacelle Temp. Avg. [°C]0.0000.0000.0000.0160.0000.0030.0000.0020.0080.0000.0110.0280.0140.0000.0040.0120.0650.0070.0410.0000.0160.0360.0230.0350.0050.0270.0190.0250.0190.0120.0000.0030.0070.0270.0070.0130.0240.0490.0510.0210.0130.0170.0170.0300.0000.0460.0400.0200.0270.0370.0320.0210.0330.0190.0140.0080.0270.0000.0100.0070.0010.0120.0130.0310.0110.0000.0170.0070.0000.0070.0140.0000.0000.0080.0000.0000.0000.0000.0311.0000.0000.0000.0220.0340.0150.0210.0180.0070.0370.0230.0000.0280.0140.0130.0360.0110.0000.010
Power factor set point0.0000.4320.9770.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0810.0240.0000.0000.0000.0000.0000.0000.0250.0170.0000.0000.0000.0000.0050.0000.0000.0020.0000.0000.0000.0690.2960.0610.0190.3780.4300.2520.0330.3560.0800.0000.0080.0001.0000.9770.0040.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0040.0000.000
Power factor set point source0.0000.4320.9770.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0810.0240.0000.0000.0000.0000.0000.0000.0250.0170.0000.0000.0000.0000.0050.0000.0000.0020.0000.0000.0000.0690.2960.0610.0190.3780.4300.2520.0330.3560.0800.0000.0080.0000.9771.0000.0040.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0040.0000.000
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.1420.0040.0250.0360.1320.0570.0500.0920.0550.3970.2260.4850.3540.0730.0340.0100.0000.0310.0330.0980.1290.0710.1150.1980.1030.0700.0250.0240.0370.0510.0400.0370.3260.2200.4210.3040.0900.0380.0470.5820.2340.2040.2360.0030.1930.1710.1900.2140.3180.2010.1890.2550.6260.4070.3940.3760.0000.0070.0000.0360.0400.0520.0180.0230.0470.0350.2520.2000.0560.6510.1420.1450.2370.0000.1580.1580.0880.0000.0220.0040.0041.0000.0290.1700.7810.0320.4090.3550.4480.0670.3410.1920.3400.2620.0630.0000.093
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0480.0000.0290.0000.0000.1160.0530.0600.0120.0960.0120.1820.1450.0230.0330.0000.0120.0000.0130.0330.0610.0370.0980.0430.0210.0330.0330.0220.0030.0000.0000.0000.0430.0050.1700.0180.0230.0250.0310.0000.1970.1700.1780.0000.2600.0820.1130.0940.2680.0700.0850.1160.1740.1410.0930.1660.0000.0020.0000.0140.0250.0330.0060.0400.0270.0330.1720.1660.5970.2470.0530.0540.1720.0000.0660.0170.0090.0070.0340.0000.0000.0291.0000.0230.0230.2080.0700.3240.1670.0000.0500.0000.1400.0160.0000.0000.000
Production LatestAverage Active Power Gen 2 Avg. [W]0.0200.0100.0000.0000.0050.0000.0980.0640.0810.0200.2380.1150.2710.2670.0080.0290.0020.0050.0290.0130.0030.0000.0440.0000.0640.0440.0090.0150.0300.0060.0040.0000.0090.0790.1630.1630.1130.0510.0380.0270.1820.3180.3220.3550.0000.4370.2450.2820.2800.4220.2260.2710.2890.2900.2480.1490.2200.0000.0000.0000.0070.0160.0210.0170.0310.0380.0130.0000.0000.3710.4870.0090.0060.0000.0000.0000.0870.0980.0120.0150.0000.0000.1700.0231.0000.1460.0690.2880.4440.1960.0080.0890.1330.1320.0960.0210.0280.000
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0140.1320.0000.0240.0510.1450.0620.0460.0770.0620.4140.2630.4410.3380.0660.0340.0000.0000.0380.0350.0940.1340.0780.1140.2070.1060.1020.0230.0260.0330.0590.0490.0430.3470.2680.3850.3110.0940.0400.0450.5670.2080.2440.2660.0060.1750.1810.1860.2250.2380.2230.1760.2580.7200.4170.4040.3800.0060.0200.0000.0400.0420.0550.0180.0240.0480.0270.2380.1920.0460.5820.1340.1330.2250.0030.1500.1380.1070.0000.0210.0000.0000.7810.0230.1461.0000.0400.3940.2370.5510.0670.3630.2370.3040.2680.0670.0000.094
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0330.0000.0000.0110.0080.0070.0030.0170.0090.0920.0270.1810.1570.0270.0000.0140.0000.0000.0130.0000.0000.0000.0300.0200.0000.0340.0150.0050.0160.0370.0360.0370.0000.0230.0290.0120.0060.0050.0060.0590.0000.0000.0000.0000.0490.0460.0110.0500.0300.0090.0020.0910.1780.2030.0570.1830.0000.0160.0170.0110.0230.0100.0100.0020.0000.0040.0940.0820.2640.0720.0310.0330.0930.0000.0310.0460.0140.0210.0180.0000.0000.0320.2080.0690.0401.0000.0460.0330.6880.0150.0110.0000.0060.0000.0120.0000.017
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0110.0210.0000.0150.0290.0520.0150.0250.0630.0420.2720.0660.4630.5100.0080.0250.0090.0000.0470.0000.0230.0330.0070.0330.0780.0540.0240.0490.0460.0080.0010.0040.0140.1430.1650.2780.3020.0670.0470.0000.3720.0690.0640.0760.0060.1270.1190.2740.1540.1090.0850.1820.1720.5340.3780.3260.4700.0000.0000.0000.0230.0030.0210.0160.0420.0770.0590.0270.0100.1760.5040.0190.0160.0270.0000.0070.0610.1050.0020.0070.0000.0000.4090.0700.2880.3940.0461.0000.1110.4000.0870.1490.1390.2060.2500.0510.0060.135
Production LatestAverage Total Active Power Avg. [W]0.0030.0740.0010.0090.0160.0080.2250.1050.0920.0440.2070.1290.1800.1650.0390.0420.0000.0000.0200.0330.0710.0750.0910.0640.0840.0560.0650.0120.0320.0000.0580.0500.0580.1560.1280.1580.1310.0520.0330.0830.2230.6150.5580.6120.0000.6490.3060.3430.3240.8570.3490.3850.3710.1990.1550.1380.1400.0000.0000.0000.0230.0660.0620.0180.0080.0190.0040.1780.1750.0980.2040.0810.0840.1640.0000.0920.1180.0980.0040.0370.0010.0010.3550.3240.4440.2370.0330.1111.0000.1550.0050.1590.1130.1260.1230.0230.0000.006
Production LatestAverage Total Reactive Power Avg. [var]0.0040.0730.0000.0210.0250.0810.0420.0380.0710.0250.3470.1530.4770.3630.0440.0120.0000.0000.0290.0100.0490.0750.0380.0990.1410.0730.0770.0340.0290.0080.0000.0000.0000.2010.1690.2790.1610.0600.0220.0150.3230.1160.1330.1490.0000.1300.1470.1180.1710.1530.1430.0970.1990.6830.4810.3350.4290.0120.0260.0090.0200.0000.0270.0050.0340.0380.0220.1370.1090.2520.4850.0760.0750.1290.0000.0870.0260.0590.0190.0230.0000.0000.4480.1670.1960.5510.6880.4000.1551.0000.0280.2030.1650.2080.1470.0330.0000.041
Reactive power generator 0,Total accumulated [var]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0150.0000.0360.0350.0000.0000.0000.0000.0000.0000.0000.0030.0000.0030.0000.0040.0120.0010.0000.0060.0000.0000.0040.0390.0040.0450.0400.0000.0000.0000.0540.0000.0000.0080.0000.0040.0000.0210.0000.0000.0000.0060.0000.0490.0220.0430.0290.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0050.0530.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0670.0000.0080.0670.0150.0870.0050.0281.0000.0320.0090.0350.0410.0060.0000.225
Rotor RPM Avg. [RPM]0.0110.0850.0000.0480.0230.1220.0970.0470.0720.0460.3300.1410.2800.2390.0430.0360.0000.0170.0390.0150.1410.2100.1260.1730.2820.1810.0910.0260.0200.0340.0400.0400.0360.7530.3880.4140.4760.0830.0330.0000.2300.1330.1190.1310.0000.1430.1550.1680.1960.1470.1420.1030.2100.2840.1660.1990.1500.0000.0000.0000.0180.0280.0240.0080.0290.0280.0280.1740.1490.0600.2750.0830.0860.1680.0000.0920.0280.0440.0130.0280.0000.0000.3410.0500.0890.3630.0110.1490.1590.2030.0321.0000.3480.3660.4290.0710.0000.045
Rotor RPM Max. [RPM]0.0090.0220.0000.0260.0320.0890.0750.0560.0400.0330.2460.2240.1670.1560.0000.0210.0080.0000.0330.0230.0860.1030.0830.1010.1420.1050.1130.0170.0160.0120.0230.0250.0230.4060.7540.1900.3140.0540.0250.0220.1490.1020.0970.1030.0000.1210.1420.1390.1760.1080.1310.0930.1530.2090.1340.1100.1130.0000.0150.0000.0080.0230.0250.0140.0100.0140.0110.0650.0540.0520.2030.0170.0200.0560.0070.0270.0000.0560.0000.0140.0000.0000.1920.0000.1330.2370.0000.1390.1130.1650.0090.3481.0000.1570.2570.0640.0000.017
Rotor RPM Min. [RPM]0.0000.0770.0000.0250.0170.0760.0690.0400.1110.0380.2480.0930.3380.2380.0340.0180.0120.0000.0250.0270.1230.1650.0990.1350.1980.1400.0330.0240.0200.0570.0410.0260.0320.3510.1750.7510.2680.0810.0490.0160.2180.0810.0670.0770.0000.0920.0650.1400.0890.1180.0470.1160.1100.2860.2080.2530.1740.0000.0120.0000.0410.0300.0280.0220.0360.0370.0280.1390.1030.1820.3580.0770.0800.1330.0000.0880.1010.0390.0100.0130.0000.0000.3400.1400.1320.3040.0060.2060.1260.2080.0350.3660.1571.0000.2260.0390.0000.042
Rotor RPM StdDev [RPM]0.0080.0870.0000.0230.0150.0810.0490.0350.0560.0760.2400.0930.2320.3680.0480.0290.0000.0000.0300.0000.0990.1390.0700.1050.1280.1100.0830.0250.0230.0100.0240.0240.0300.4390.2970.2670.7130.0690.0200.0090.2230.1040.1090.1150.0000.1350.1700.2290.2070.1220.1520.1720.2350.2090.1240.1560.2250.0050.0000.0020.0100.0040.0200.0060.0190.0320.0340.1530.1220.0150.2040.0810.0780.1480.0050.0770.0210.0870.0200.0360.0000.0000.2620.0160.0960.2680.0000.2500.1230.1470.0410.4290.2570.2261.0000.0500.0120.045
Spinner Temp. Avg. [°C]0.0160.0280.0040.0190.0090.0150.0150.0000.0280.0100.0440.0270.0530.0480.0000.0690.0170.0000.0120.0000.0130.0310.0140.0300.0480.0390.0430.0150.0140.0000.0000.0000.0000.0700.0790.0510.0620.0300.0240.0150.0420.0250.0260.0250.0030.0180.0190.0270.0230.0210.0240.0320.0310.0610.0480.0520.0470.0000.0000.0000.0040.0080.0090.0100.0300.0000.0120.0290.0270.0140.0480.0330.0340.0280.0000.0380.0240.0000.0000.0110.0040.0040.0630.0000.0210.0670.0120.0510.0230.0330.0060.0710.0640.0390.0501.0000.0000.000
Total Active power [W]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0210.0110.0000.0000.0000.0000.0000.0000.0000.0040.0150.0070.0000.0000.0350.0000.0000.0140.0000.0000.0000.0290.0000.0000.0000.0000.0160.0000.0000.0190.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0280.0000.0000.0060.0000.0000.0000.0000.0000.0000.0120.0001.0000.000
Total reactive power [var]0.0000.0000.0000.0060.0000.0000.0000.0000.0000.0080.0220.0000.0490.0660.0000.0000.0000.0000.0130.0000.0160.0120.0030.0000.0170.0040.0040.0000.0050.0000.0000.0000.0110.0410.0130.0660.0530.0030.0170.0130.0650.0000.0000.0100.0000.0040.0040.0180.0000.0000.0090.0000.0000.0660.0350.0510.0590.0030.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0810.0000.0000.0000.0000.0000.0070.0080.0000.0100.0000.0000.0930.0000.0000.0940.0170.1350.0060.0410.2250.0450.0170.0420.0450.0000.0001.000

Missing values

2025-05-15T14:15:39.405821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-15T14:15:40.258388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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92020-01-01 01:30:0000000001000000000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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